Bock, S.; Weiß, M.  G. (2019): Non-Convergence and Limit Cycles in the Adam optimizer. In: International Conference on Artificial Neural Networks ICANN 2019. München: Springer, 232-243.

Bock, S.; Weiß, M.  G. (2019): A Proof of Local Convergence for the Adam Optimizer. In: International Joint Conference on Neural Networks IJCNN 2019. Budapest, 1--8.

Weiß, M. G.  (2019): Optimal Object Placement Using a Virtual Axis. In: Jadran Lenarcic und Vicenzo Parenti-Castelli: Advances in robot kinematics 2018, Bd. 8. Cham: Springer (Springer Proceedings in Advanced Robotics, 8), S. 116–123.

Weiß, M. G. (2018): Optimization of Robot Tasks with Cartesian Degrees of Freedom using Virtual Joints. In: 3. OTH-Clusterkonferenz. OTH Regensburg / OTH Amberg-Weiden, S. 75–79.

Bock, S.; Goppold, J.; Weiß, M. G. (2018): An improvement of the convergence proof of the ADAM-Optimizer. In: 3. OTH-Clusterkonferenz. OTH Regensburg / OTH Amberg-Weiden, S. 80–84.

Volbert, K.; Weiß, M. G. (2017): Intelligente Steuerung von Industrierobotern. In: 2. OTH-Clusterkonferenz. OTH Regensburg / OTH Amberg-Weiden, S. 16–19.

Bock, S.; Weiß, M. G. (2017): Lösung der Rückwärtskinematik mit Homotopie-Methoden. In: 2. OTH-Clusterkonferenz. OTH Regensburg / OTH Amberg-Weiden, S. 24–27.

Weiß, M. G. (2015): A Class of 6R Robots and Poses with 16 Analytical Solutions. In: Proceedings of the IMA Conference on Mathematics of Robotics. IMA Conference on Mathematics of Robotics, 9th September 2015: Institute of Mathematics and its Applications.

Kurze, M.; Weiß, M.; Otter, M.  (2006): Methods and tools to design and test robot control systems. In: Proceedings of the Joint Conference on Robotics: ISR 2006, 37th International Symposium on Robotics and Robotik 2006, 4th German Conference on Robotics; Düsseldorf: VDI-Wissensforum-IWB-GmbH (VDI-Berichte), S. 271–278.

Townley, S.; Ilchmann, A.; Weiss, M. G.; McClements, W.; Ruiz, A. C.; Owens, D. H.; Prätzel-Wolters, D. (2000): Existence and learning of oscillations in recurrent neural networks. In: IEEE Trans. Neural Netw. 11 (1), S. 205–214. DOI: 10.1109/72.822523.

Weiß, M.  G. (1998): Learning Periodic Signals with Discrete Time Neural Networks. In: Alessandro Beghi (Hg.): Proceedings of the MTNS-98 Symposium: Mathematical Theory of Networks and Systems. Padova: S. 961–964.

Weiß, M.  G. (1998): Learning periodic signals with recurrent neural networks. In: Z. angew. Math. Mech. 78 (S3), S. 1131–1132. DOI: 10.1002/zamm.199807815130.

Weiß, M.  G. (1999): Regulation Thermography and Long-Term ECGs: Mathematical Diagnosis Aiding in Medicine. In: Proceedings of the International Congress on Industrial and Applied Mathematics ICIAM 99, Edinburgh. Oxford, New York: Oxford University Press (VDI-Berichte), S. 147.

Weiß, M. G. (1999): Learning periodic signals with recurrent neural networks. Zugl.: Kaiserslautern, Univ., Diss., 1999. Aachen: Shaker (Berichte aus der Mathematik).

Weiß, M. G. (1997): Learning oscillations using adaptive control. In: Wulfram Gerstner, Alain Germond, M.  Hasler und Jean-Daniel Nicoud (Hg.): Artificial Neural Networks ‐- ICANN’97. Berlin, Heidelberg: Springer Berlin Heidelberg, S. 331–336.